ArticleEvidence-based mental health2021
Prediction of treatment dosage and duration from free-text prescriptions: an application to ADHD medications in the Swedish prescribed drug register.
Article in Evidence-based mental health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 25 citations in OpenAlex.
- Treatment Outcomes With Licensed and Unlicensed Stimulant Doses for Adults With Attention-Deficit/Hyperactivity Disorder: A Systematic Review and Meta-Analysis.JAMA psychiatry · 2024Pooled it
- Adherence, frequency, and long-term follow-up of video game-based treatments in patients with attention-deficit/hyperactivity disorder: A systematic review.Brain and behavior · 2023Pooled it
- Feasibility of a Monthly Morphine Milligram Equivalent Metric for Opioid Surveillance Using the National Claims Database of Japan: A Repeated Cross-Sectional Study in a Low-Consumption Setting.Therapeutic innovation & regulatory science · 2026Article
- Medication Adherence in Children and Adults Receiving Treatment for Attention Deficit Hyperactivity Disorder (ADHD) in Sweden: A Nationwide Study.Journal of attention disorders · 2026Article
- Discontinuation and reinitiation of pharmacological treatment for ADHD among individuals with ADHD and substance use disorder.BMJ mental health · 2026Article
- Duration of ADHD medication treatment among Finnish children and adolescents ‒ a nationwide register study.European child & adolescent psychiatry · 2025Article
- Prescribed opioid analgesic use in pregnancy and risk of neurodevelopmental disorders in children: A retrospective study in Sweden.PLoS medicine · 2025Article
- Artificial intelligence in drug resistance management.3 Biotech · 2025Review
- Cumulative ADHD medication use and risk of type 2 diabetes in adults: a Swedish Register study.BMJ mental health · 2024Article
- Structuring medication signeturs as a language regression task: comparison of zero- and few-shot GPT with fine-tuned models.JAMIA open · 2024Article
- Attention-Deficit/Hyperactivity Disorder Medications and Long-Term Risk of Cardiovascular Diseases.JAMA psychiatry · 2024Article
- Predicting Patients' Satisfaction With Mental Health Drug Treatment Using Their Reviews: Unified Interchangeable Model Fusion Approach.JMIR mental health · 2023Article
- Use of hormonal contraceptives and antidepressants and risks of suicidal behavior and accidents among women with premenstrual disorders: a nationwide cohort study.BMC medicine · 2022Article
- Risk prediction model for cardiovascular diseases in adults initiating pharmacological treatment for attention-deficit/hyperactivity disorder.Evidence-based mental health · 2022Article
- Carpe diem.Evidence-based mental health · 2022Article
- Kidney function and prescribed dose in middle-aged and older patients starting selective serotonin reuptake inhibitors.Pharmacoepidemiology and drug safety · 2022Article
- Article
- Association Between Pharmacological Treatment of Attention-Deficit/Hyperactivity Disorder and Long-term Unemployment Among Working-Age Individuals in Sweden.JAMA network open · 2022Article
- Pharmacological and non-pharmacological interventions for adults with ADHD: protocol for a systematic review and network meta-analysis.BMJ open · 2022Article
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAccurate estimation of daily dosage and duration of medication use is essential to pharmacoepidemiological studies using electronic healthcare databases. However, such information is not directly available in many prescription databases, including the Swedish Prescribed Drug Register.
objectiveTo develop and validate an algorithm for predicting prescribed daily dosage and treatment duration from free-text prescriptions, and apply the algorithm to ADHD medication prescriptions.
methodsWe developed an algorithm to predict daily dosage from free-text prescriptions using 8000 ADHD medication prescriptions as the training sample, and estimated treatment periods while taking into account several features including titration, stockpiling and non-perfect adherence. The algorithm was implemented to all ADHD medication prescriptions from the Swedish Prescribed Drug Register in 2013. A validation sample of 1000 ADHD medication prescriptions, independent of the training sample, was used to assess the accuracy for predicted daily dosage.
findingsIn the validation sample, the overall accuracy for predicting daily dosage was 96.8%. Specifically, the natural language processing model (NLP1 and NLP2) have an accuracy of 99.2% and 96.3%, respectively. In an application to ADHD medication prescriptions in 2013, young adult ADHD medication users had the highest probability of discontinuing treatments as compared with other age groups. The daily dose of methylphenidate use increased with age substantially.
conclusionsThe algorithm provides a flexible approach to estimate prescribed daily dosage and treatment duration from free-text prescriptions using register data. The algorithm showed a good performance for predicting daily dosage in external validation. CLINICAL IMPLICATIONS: The structured output of the algorithm could serve as basis for future pharmacoepidemiological studies evaluating utilization, effectiveness, and safety of medication use, which would facilitate evidence-based treatment decision-making.
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